A novel shift in the glass transition temperature of polymer nanocomposites: a molecular dynamics simulation study

Distribution of Mechanical Properties in Poly(ethylene oxide)/silica Nanocomposites via Atomistic Simulations: From the Glassy to the Liquid State

Polymer nanocomposites exhibit a heterogeneous mechanical behavior that is strongly dependent on the interaction between the polymer matrix and the nanofiller. Here, we provide a detailed investigation of the mechanical response of model polymer nanocomposites under deformation, across a range of temperatures, from the glassy regime to the liquid one, via atomistic molecular dynamics simulations. We study the poly(ethylene oxide) matrix with silica nanoparticles (PEO/SiO2) as a model polymer nanocomposite system with attractive polymer/nanofiller interactions. Probing the properties of polymer chains at the molecular level reveals that the effective mass density of the matrix and interphase regions changes during deformation. This decrease in density is much more pronounced in the glassy state. We focus on factors that govern the mechanical response of PEO/SiO2 systems by investigating the distribution of the (local) mechanical properties, focusing on the polymer/nanofiller interphase and matrix regions. As expected when heating the system, a decrease in Young's modulus is observed, accompanied by an increase in Poisson's ratio. The observed differences regarding the rigidity between the interphase and the matrix region decrease as the temperature rises; at temperatures well above the glass-transition temperature, the rigidity of the interphase approaches the matrix one. To describe the nonlinear viscoelastic behavior of polymer chains, the elastic modulus of the PEO/SiO2 systems is further calculated as a function of the strain for the entire nanocomposite, as well as the interphase and matrix regions. The elastic modulus drops dramatically with increasing strain for both the matrix and the interphase, especially in the small-deformation regime. We also shed light on characteristic structural and dynamic attributes during deformation. Specifically, we examine the rearrangement behavior as well as the segmental and center-of-mass dynamics of polymer chains during deformation by probing the mobility of polymer chains in both axial and radial motions under deformation. The behavior of the polymer motion in the axial direction is dominated by the deformation, particularly at the interphase, whereas a more pronounced effect of the temperature is observed in the radial directions for both the interphase and matrix regions.

Assessing the impact of ultra-thin diamond nanothreads on the glass transition temperature of a bituminous binder

Low-temperature cracking and rutting are the most destructive problems of bitumen that hinder the application of high-performance bitumen engineering, which is dependent on its glass transition temperature (Tg). Through in silico studies, this work has systematically investigated the Tg of a bituminous binder with the addition of diamond nanothread (DNT) fillers with varying filler content, alignment, distribution, and functional groups. In general, the glass transition phenomenon of the bitumen is determined by the mobility of its constituent molecules. Tg is found to increase gradually with the increase in the weight percentage of DNT and then decreases when the weight percentage exceeds 5.05 wt%. The enhancement effect on Tg is weakened when DNTs are distributed vertically or functionalized with functional groups. Specifically, DNT fillers induce inhomogeneity, which promotes the motion of small molecules while hindering the motion of large molecules. The aggregation of DNTs and the molecular environment in the vicinity of DNTs directly affect Tg. In summary, aggregation and adhesion are the dominant mechanisms affecting the mobility of the constituent molecules in the DNT/bitumen system and thus its glass transition temperature. This work provides in-depth insights into the underlying mechanisms for the glass transition of a bituminous binder, which could serve as theoretical guidance for tuning the low-temperature performance of the bituminous binder.

The Role of Polymer Chain Stiffness and Guest Nanoparticle Loading in Improving the Glass Transition Temperature of Polymer Nanocomposites

The impact of polymer chain stiffness characterized by the bending modulus (k_θ) on the glass transition temperature (T_g) of pure polymer systems, as well as polymer nanocomposites (PNCs), is investigated using molecular dynamics simulations. At small k_θ values, the pure polymer system and respective PNCs are in an amorphous state, whereas at large k_θ values, both systems are in a semicrystalline state with a glass transition at low temperature. For the pure polymer system, T_g initially increases with k_θ and does not change obviously at large k_θ. However, the T_g of PNCs shows interesting behaviors with the increasing volume fraction of nanoparticles (f_NP) at different k_θ values. T_g tends to increase with f_NP at small k_θ, whereas it becomes suppressed at large k_θ.

A simulation study on the subdiffusion of polymer chains in crowded environments containing nanoparticles

Polymer chains in crowded environments often show subdiffusive behavior. We adopt molecular dynamics simulations to study the conditions for the subdiffusion of polymer chains in crowded environments containing randomly distributed, immobile, attractive nanoparticles (NPs). The attraction is strong enough to adsorb polymer chains on NPs. The results show that subdiffusion occurs at a low concentration of polymer chains (c_p). A transition from subdiffusion to normal diffusion is observed when c_p exceeds the transition concentration , which increases with increasing concentration of NPs while decreases with increasing size of NPs. The high concentration and small size of NPs exert a big effect on the subdiffusion of polymer chains. The subdiffusive behavior of polymer chains can be attributed to the strong adsorption of polymer chains on the attractive NPs. For the subdiffusion case, polymer chains are adsorbed strongly on multiple NPs, and they diffuse via the NP-exchange diffusion mechanism. However for the normal diffusion case, polymer chains are either free or weakly adsorbed on one or a few NPs, and they diffuse mainly via the adsorption-and-desorption diffusion mechanism.

A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers

Solubility of gas in polymers is an important physico-chemical property of foam materials and widely used in the preparation and modification of new materials. Under the conditions of high temperature and high pressure, the dissolution process is a nonlinear, non-equilibrium and dynamic process, so it is difficult to establish an accurate solubility calculation model. Inspired by particle dynamics and evolutionary algorithm, this paper proposes a hybrid model based on chaotic self-adaptive particle dynamics evolutionary algorithm (CSA-PD-EA), which can use the iterative process of particles in evolutionary algorithms at the dynamic level to simulate the mutual diffusion process of molecules during dissolution. The predicted solubility of supercritical CO₂ in poly(d,l-lactide-co-glycolide), poly(l-lactide) and poly(vinyl acetate) indicated that the comprehensive prediction performance of the CSA-PD-EA model was high. The calculation error and correlation coefficient were, respectively, 0.3842 and 0.9187. The CSA-PD-EA model showed prominent advantages in accuracy, efficiency and correlation over other computational models, and its calculation time was 4.144-15.012% of that of other dynamic models. The CSA-PD-EA model has wide application prospects in the computation of physical and chemical properties and can provide the basis for the theoretical calculation of multi-scale complex systems in chemistry, materials, biology and physics.

A Novel Biodegradable Composite Polymer Material Based on PLGA and Silver Oxide Nanoparticles with Unique Physicochemical Properties and Biocompatibility with Mammalian Cells

A method for obtaining a stable colloidal solution of silver oxide nanoparticles has been developed using laser ablation. The method allows one to obtain nanoparticles with a monomodal size distribution and a concentration of more than 108 nanoparticles per mL. On the basis of the obtained nanoparticles and the PLGA polymer, a nanocomposite material was manufactured. The manufacturing technology allows one to obtain a nanocomposite material without significant defects. Nanoparticles are not evenly distributed in the material and form domains in the composite. Reactive oxygen species (hydrogen peroxide and hydroxyl radical) are intensively generated on the surfaces of the nanocomposite. Additionally, on the surface of the composite material, an intensive formation of protein long-lived active forms is observed. The ELISA method was used to demonstrate the generation of 8-oxoguanine in DNA on the developed nanocomposite material. It was found that the multiplication of microorganisms on the developed nanocomposite material is significantly decreased. At the same time, the nanocomposite does not inhibit proliferation of mammalian cells. The developed nanocomposite material can be used as an affordable and non-toxic nanomaterial to create bacteriostatic coatings that are safe for humans.

A simulation study on the effect of nanoparticle size on the glass transition temperature of polymer nanocomposites

The effect of the size of nanoparticles, σ_NP, on the glass transition temperature, T_g, of polymer nanocomposites is studied by using molecular dynamics simulations. The variation of T_g with σ_NP shows two distinct behaviours for polymer nanocomposites at low and high volume fractions of nanoparticles (f_NP). At a low f_NP, T_g decays almost exponentially with σ_NP, whereas at a high f_NPT_g shows a complex behaviour: it initially increases and then decreases with increasing σ_NP. The decrease in T_g with σ_NP is due to the significant decrease of adsorbed polymer monomers, while the increase in T_g with σ_NP is attributed to the slower diffusion of larger nanoparticles. We have also investigated the diffusion and relaxation of polymer chains at a temperature above T_g for both low and high f_NPs. The diffusion constant and relaxation time of polymer chains are highly consistent with the behaviour of T_g.